In recent years, as a user quantity and a data amount explosively grow, a distributed architecture has increasingly become an infrastructure of many information technology (IT) enterprise platforms. Reliable low-cost large platforms, for example, a distributed computing platform and a distributed storage system, are constructed by stacking massive low-cost computing servers and storage servers. In these large platforms, a cluster is one of core technologies.
The cluster is a distributed collaboration technology, and a group for a collaborative operation is formed by massive nodes to complete a target task on a huge scale quickly and reliably. Based on a group operation, for the cluster, migration of a task on a faulty node and load balancing between nodes need to be considered in order to ensure that a cluster group reliably operates for a long time. A core of fault-based migration and balance balancing technologies is a scheduling algorithm, for example, a fault-based migration algorithm and a load balancing algorithm. The algorithm determines pressure balancing between nodes in the cluster group, avoiding a fault or long-time overload running of the entire cluster resulting from a fault or overload of an individual node.
In the security surveillance field, to meet a large-scale networking requirement of Safe City and a large campus, many network video recorders (NVR) are stacked for centralized management and maintenance. As a user imposes a higher requirement for reliability of video recording, a collaborative cluster is further constructed on a basis of stacking to form a reliable large-capacity video surveillance cloud platform.
Currently, in the video surveillance field, a video surveillance system is divided into a front end and a rear end. As shown in FIG. 1A, the front end is an Internet Protocol camera (IPC) configured to collect a real-time image and transmit a video stream to a rear NVR for forwarding and storage. The rear end is the NVR configured to access and control multiple IPCs in a centralized manner, obtain video streams of the IPCs, and forward and distribute the video streams to multiple users of a surveillance platform. In addition, the NVR has a large-capacity built-in storage or an external large disk array, and can store a recorded video in the surveillance platform for subsequent playback, download, and backup.
It can be learned that all IPCs are connected to the NVR and transmit bitstreams collected by the IPCs to the NVR for recording and storage. This requires that the NVR have a relatively strong access capability and sufficient storage space. Especially for the storage space, with the high-definition, 4000 pixels based (4K-based), and intelligent development, the NVR occupies more storage space. A single NVR cannot support bitstream storage of massive cameras. Therefore, a stacked networking mode is derived. As shown in FIG. 1B, in stacked networking, all NVRs are managed in a centralized manner, and a unified service entrance is provided, thereby solving difficulties such as centralized service access and device management in a large Safe City project. In addition, in the stacked networking, scale-out and dynamic scaling capabilities are further provided. When an IPC quantity increases, a new NVR may be added to access a new IPC. When the IPC quantity decreases, a user may reduce existing NVRs to decrease operating costs.
However, computing capabilities and storage space of NVRs are different. Therefore, in the stacked networking, load balancing cannot be implemented according to existing capabilities of all NVRs.